Suppose you are working as a database administrator in a company which has a huge database that changes frequently. A lot of transactions, searches and DML operations are being processed daily. A database file can be organized in different ways to support multiple operations. Each file organization technique has benefits on other due to some characteristics.

The main concern at the company is scanning and insertion operations. Every user in the company searches the records according to his/her own needs. Some of them need the records based on range while other searches on some particular field. You can store database using B+ tree or hash indexed file.

Keeping in view the above scenario, which type of indexing would you choose? Support your choice with logical arguments.

B-tree

No index structure can satisfy all needs, but the self-balancing B-tree index comes closest to optimizing the performance of searches on large sets of data. Each B-tree node holds multiple keys and pointers. The maximum number of keys in a node supported by a specific B-tree is the order of that tree. Each node has a potential of order+1 pointers to the level below it. For example, the order=2 B-tree illustrated in Figure 7-1 has tree pointers: to child nodes whose value is less than the first key, to the child nodes whose value is greater than the first key and less than the second key, and to the child nodes whose value is greater than the second key. Thus, the B-tree algorithm minimizes the number of reads and writes necessary to locate a record by passing through fewer nodes than in a binary tree algorithm, which has only one key and at most two children for each decision node. Here we describe the Knuth variation in which the index consists of two parts: a sequence set that provides fast sequential access to the data, and an index set that provides direct access to the sequence set.

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